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Surface-attached cells can sense and respond to shear flow, but planktonic (free-swimming) cells are typically assumed to be oblivious to any flow that carries them. Here, we find that planktonic bacteria can transcriptionally respond to flow, inducing expression changes that are beneficial in flow. Specifically, we use microfluidic experiments and quantitative modeling to show that in the presence of flow, planktonicPseudomonas aeruginosainduce shear rate–dependent genes that promote growth in low-oxygen environments. Untangling this mechanism revealed that in flow, motileP. aeruginosaspatially redistribute, leading to cell density changes that activate quorum sensing, which in turn enhances the oxygen uptake rate. In diffusion-limited environments, including those commonly encountered by bacteria, flow-induced cell density gradients also independently generate oxygen gradients that alter gene expression. Mutants deficient in this flow-responsive mechanism exhibit decreased fitness in flow, suggesting that this dynamic coupling of biological and mechanical processes can be physiologically significant. 

The retractile type IV pilus (T4P) is important for virulence of the opportunistic human pathogenPseudomonas aeruginosa. The single-stranded RNA (ssRNA) phage PP7 binds to T4P and is brought to the cell surface through pilus retraction. Using fluorescence microscopy, we discovered that PP7 detaches T4P, which impairs cell motility and restricts the pathogen’s virulence. Using cryo–electron microscopy, mutagenesis, optical trapping, and Langevin dynamics simulation, we resolved the structure of PP7, T4P, and the PP7/T4P complex and showed that T4P detachment is driven by the affinity between the phage maturation protein and its bound pilin, plus the pilus retraction force and speed, and pilus bending. Pilus detachment may be widespread among other ssRNA phages and their retractile pilus systems and offers new prospects for antibacterial prophylaxis and therapeutics. 

ABSTRACT The crowded bacterial cytoplasm is comprised of biomolecules that span several orders of magnitude in size and electrical charge. This complexity has been proposed as the source of the rich spatial organization and apparent anomalous diffusion of intracellular components, although this has not been tested directly. Here, we use biplane microscopy to track the 3D motion of self-assembled bacterial Genetically Encoded Multimeric nanoparticles (bGEMs) with tunable size (20 to 50 nm) and charge (−2160 to +1800 e) in liveEscherichia colicells. To probe intermolecular details at spatial and temporal resolutions beyond experimental limits, we also developed a colloidal whole-cell model that explicitly represents the size and charge of cytoplasmic macromolecules and the porous structure of the bacterial nucleoid. Combining these techniques, we show that bGEMs spatially segregate by size, with small 20-nm particles enriched inside the nucleoid, and larger and/or positively charged particles excluded from this region. Localization is driven by entropic and electrostatic forces arising from cytoplasmic polydispersity, nucleoid structure, geometrical confinement, and interactions with other biomolecules including ribosomes and DNA. We observe that at the timescales of traditional single molecule tracking experiments, motion appears sub-diffusive for all particle sizes and charges. However, using computer simulations with higher temporal resolution, we find that the apparent anomalous exponents are governed by the region of the cell in which bGEMs are located. Molecular motion does not display anomalous diffusion on short time scales and the apparent sub-diffusion arises from geometrical confinement within the nucleoid and by the cell boundary. 

Abstract Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studiedE. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200E. coliproteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway inE. coliremains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates inE. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis. 

Abstract Bacterial populations are highly adaptive. They can respond to stress and survive in shifting environments. How the behaviours of individual bacteria vary during stress, however, is poorly understood. To identify and characterize rare bacterial subpopulations, technologies for single-cell transcriptional profiling have been developed. Existing approaches show some degree of limitation, for example, in terms of number of cells or transcripts that can be profiled. Due in part to these limitations, few conditions have been studied with these tools. Here we develop massively-parallel, multiplexed, microbial sequencing (M3-seq)—a single-cell RNA-sequencing platform for bacteria that pairs combinatorial cell indexing with post hoc rRNA depletion. We show that M3-seq can profile bacterial cells from different species under a range of conditions in single experiments. We then apply M3-seq to hundreds of thousands of cells, revealing rare populations and insights into bet-hedging associated with stress responses and characterizing phage infection. 

Abstract In mammals, subcellular protein localization of factors like planar cell polarity proteins is a key driver of the multicellular organization of tissues. Bacteria also form organized multicellular communities, but these patterns are largely thought to emerge from regulation of whole-cell processes like growth, motility, cell shape, and differentiation. Here we show that a unique intracellular patterning of appendages known as type IV pili (T4P) can drive multicellular development of complex bacterial communities. Specifically, dynamic T4P appendages localize in a line along the long axis of the cell in the bacterium Acinetobacter baylyi . This long-axis localization is regulated by a functionally divergent chemosensory Pil-Chp system, and an atypical T4P protein homologue (FimV) bridges Pil-Chp signaling and T4P positioning. We further demonstrate through modeling and empirical approaches that subcellular T4P localization controls how individual cells interact with one another, independently of T4P dynamics, with different patterns of localization giving rise to distinct multicellular architectures. Our results reveal how subcellular patterning of single cells regulates the development of multicellular bacterial communities. 

The ability of eukaryotic cells to differentiate surface stiffness is fundamental for many processes like stem cell development. Bacteria were previously known to sense the presence of surfaces, but the extent to which they could differentiate stiffnesses remained unclear. Here we establish that the human pathogen Pseudomonas aeruginosa actively measures surface stiffness using type IV pili (TFP). Stiffness sensing is nonlinear, as induction of the virulence factor regulator is peaked with stiffness in a physiologically important range between 0.1 kPa (similar to mucus) and 1,000 kPa (similar to cartilage). Experiments on surfaces with distinct material properties establish that stiffness is the specific biophysical parameter important for this sensing. Traction force measurements reveal that the retraction of TFP is capable of deforming even stiff substrates. We show how slow diffusion of the pilin PilA in the inner membrane yields local concentration changes at the base of TFP during extension and retraction that change with substrate stiffness. We develop a quantitative biomechanical model that explains the transcriptional response to stiffness. A competition between PilA diffusion in the inner membrane and a loss/gain of monomers during TFP extension/retraction produces substrate stiffness-dependent dynamics of the local PilA concentration. We validated this model by manipulating the ATPase activity of the TFP motors to change TFP extension and retraction velocities and PilA concentration dynamics, altering the stiffness response in a predictable manner. Our results highlight stiffness sensing as a shared behavior across biological kingdoms, revealing generalizable principles of environmental sensing across small and large cells. 

Type IV pili (TFP) function through cycles of extension and retraction. The coordination of these cycles remains mysterious due to a lack of quantitative measurements of multiple features of TFP dynamics. Here, we fluorescently label TFP in the pathogenPseudomonas aeruginosaand track full extension and retraction cycles of individual filaments. Polymerization and depolymerization dynamics are stochastic; TFP are made at random times and extend, pause, and retract for random lengths of time. TFP can also pause for extended periods between two extension or two retraction events in both wild-type cells and a slowly retracting PilT mutant. We developed a biophysical model based on the stochastic binding of two dedicated extension and retraction motors to the same pilus machine that predicts the observed features of the data with no free parameters. We show that only a model in which both motors stochastically bind and unbind to the pilus machine independent of the piliation state of the machine quantitatively explains the experimentally observed pilus production rate. In experimental support of this model, we show that the abundance of the retraction motor dictates the pilus production rate and that PilT is bound to pilus machines even in their unpiliated state. Together, the strong quantitative agreement of our model with a variety of experiments suggests that the entire repetitive cycle of pilus extension and retraction is coordinated by the competition of stochastic motor binding to the pilus machine, and that the retraction motor is the major throttle for pilus production.